John J. Alam

41 papers receiving 5.3k citations

John J. Alam's Hit Papers

Telaprevir with Peginterferon and Ribavirin for Chronic HCV Genotype 1 Infection 2009 · 893 citations
8930+10+20Years since publication50010001.5k2.0k

Peers

John J. Alam
Comparison fields: 5 of 108
  • Hepatology 2.0k
  • Pathology and Forensic Medicine 2.4k
  • Rheumatology 912
  • Neurology 881
  • Epidemiology 1.2k
Replace Tejas S Shah with:
Tejas S Shah United Kingdom
Dietrich von Schweinitz Germany
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Christopher R. Bolen United States
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Citations per field
00.5×2×4×6×8.3×
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Citations per year

Countries citing papers authored by John J. Alam

Since Specialization
Citations

This map shows the geographic impact of John J. Alam's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John J. Alam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John J. Alam more than expected).

Fields of papers citing papers by John J. Alam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John J. Alam. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John J. Alam. The network helps show where John J. Alam may publish in the future.

Co-authors

The 25 scholars most cited alongside John J. Alam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John J. Alam Line = papers co-authored together John J. Alam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Intramuscular interferon beta‐1a for disease progression in relapsing multiple sclerosis
Hit paper breakdown →
19962072
2
Telaprevir with Peginterferon and Ribavirin for Chronic HCV Genotype 1 Infection
Hit paper breakdown →
2009893
3
Telaprevir and Peginterferon with or without Ribavirin for Chronic HCV Infection
Hit paper breakdown →
2009856
4 2006325
5 1998291
6 1996214
7 1997198
8 202183
9 201574
10 201855
11 201753
12 199752
13 201450
14 199749
15 202247
16 200335
17 202035
18 201230
19 200529
20 199427

About John J. Alam

John J. Alam is a scholar working on Hepatology, Rheumatology, Pathology and Forensic Medicine, Physiology and Pharmacology, having authored 46 papers that have together received 5.7k indexed citations. Recurring topics across this work include Hepatitis C virus research (11 papers), Multiple Sclerosis Research Studies (7 papers), Alzheimer's disease research and treatments (7 papers), Systemic Lupus Erythematosus Research (7 papers), Cholinesterase and Neurodegenerative Diseases (6 papers), Retinal Development and Disorders (4 papers), Cytokine Signaling Pathways and Interactions (4 papers) and Neuroinflammation and Neurodegeneration Mechanisms (3 papers). The work is most often cited by research in Hepatology (2.0k citations), Pathology and Forensic Medicine (2.4k citations), Rheumatology (912 citations), Neurology (881 citations) and Epidemiology (1.2k citations). John J. Alam has collaborated with scholars based in United States, Netherlands and France. Frequent co-authors include Lindsay A. McNair, Robert S. Kauffman, John G. McHutchison, Stuart C. Gordon, Andrew Joseph Muir, Ira M. Jacobson, Gregory T. Everson, Mark Sulkowski, Stefan Zeuzem and Nicole Forestier. Their work appears in journals such as Alzheimer s & Dementia, Neurology, Annals of Neurology, Annals of Clinical and Translational Neurology and Gastroenterology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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